Prayogo, Doddy and Tjong, Wong Foek and Tjandra, Daniel (2018) Prediction of High-Performance Concrete Strength Using a Hybrid Artificial Intelligence Approach. [UNSPECIFIED]
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Abstract
This study introduces an improved artificial intelligence (AI) approach called intelligence optimized support vector regression (IO-SVR) for estimating the compressive strength of high-performance concrete (HPC). The nonlinear functional mapping between the HPC materials and compressive strength is conducted using the AI approach. A dataset with 1,030 HPC experimental tests is used to train and validate the prediction model. Depending on the results of the experiments, the forecast outcomes of the IO-SVR model are of a much higher quality compared to the outcomes of other AI approaches. Additionally, because of the high-quality learning capabilities, the IO-SVR is highly recommended for calculating HPC strength.
| Item Type: | UNSPECIFIED |
|---|---|
| Uncontrolled Keywords: | - |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Faculty of Civil Engineering and Planning > Civil Engineering Department |
| Depositing User: | Admin |
| Date Deposited: | 04 Nov 2018 21:25 |
| Last Modified: | 26 Nov 2018 14:03 |
| URI: | https://repository.petra.ac.id/id/eprint/18013 |
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